Overview

Dataset statistics

Number of variables15
Number of observations940
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory110.3 KiB
Average record size in memory120.1 B

Variable types

Numeric14
Categorical1

Alerts

Calories is highly overall correlated with TotalDistance and 3 other fieldsHigh correlation
FairlyActiveMinutes is highly overall correlated with ModeratelyActiveDistance and 5 other fieldsHigh correlation
LightActiveDistance is highly overall correlated with LightlyActiveMinutes and 3 other fieldsHigh correlation
LightlyActiveMinutes is highly overall correlated with LightActiveDistance and 3 other fieldsHigh correlation
ModeratelyActiveDistance is highly overall correlated with FairlyActiveMinutes and 5 other fieldsHigh correlation
TotalDistance is highly overall correlated with Calories and 8 other fieldsHigh correlation
TotalSteps is highly overall correlated with Calories and 8 other fieldsHigh correlation
TrackerDistance is highly overall correlated with Calories and 8 other fieldsHigh correlation
VeryActiveDistance is highly overall correlated with FairlyActiveMinutes and 5 other fieldsHigh correlation
VeryActiveMinutes is highly overall correlated with Calories and 6 other fieldsHigh correlation
ActivityDate is uniformly distributedUniform
TotalSteps has 77 (8.2%) zerosZeros
TotalDistance has 78 (8.3%) zerosZeros
TrackerDistance has 78 (8.3%) zerosZeros
LoggedActivitiesDistance has 908 (96.6%) zerosZeros
VeryActiveDistance has 413 (43.9%) zerosZeros
ModeratelyActiveDistance has 386 (41.1%) zerosZeros
LightActiveDistance has 85 (9.0%) zerosZeros
SedentaryActiveDistance has 858 (91.3%) zerosZeros
VeryActiveMinutes has 409 (43.5%) zerosZeros
FairlyActiveMinutes has 384 (40.9%) zerosZeros
LightlyActiveMinutes has 84 (8.9%) zerosZeros

Reproduction

Analysis started2026-01-09 11:30:04.770979
Analysis finished2026-01-09 11:30:12.512377
Duration7.74 seconds
Software versionydata-profiling vv4.18.0
Download configurationconfig.json

Variables

Id
Real number (ℝ)

Distinct33
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8554074 × 109
Minimum1.5039604 × 109
Maximum8.8776894 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:12.539964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.5039604 × 109
5-th percentile1.6245801 × 109
Q12.320127 × 109
median4.445115 × 109
Q36.9621811 × 109
95-th percentile8.7920097 × 109
Maximum8.8776894 × 109
Range7.373729 × 109
Interquartile range (IQR)4.6420541 × 109

Descriptive statistics

Standard deviation2.4248055 × 109
Coefficient of variation (CV)0.4994031
Kurtosis-1.2730307
Mean4.8554074 × 109
Median Absolute Deviation (MAD)2.418763 × 109
Skewness0.1771249
Sum4.5640829 × 1012
Variance5.8796816 × 1018
MonotonicityIncreasing
2026-01-09T17:00:12.572921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
150396036631
 
3.3%
431970357731
 
3.3%
858381505931
 
3.3%
837856320031
 
3.3%
805347532831
 
3.3%
708636192631
 
3.3%
696218106731
 
3.3%
555395744331
 
3.3%
470292168431
 
3.3%
455860992431
 
3.3%
Other values (23)630
67.0%
ValueCountFrequency (%)
150396036631
3.3%
162458008131
3.3%
164443008130
3.2%
184450507231
3.3%
192797227931
3.3%
202248440831
3.3%
202635203531
3.3%
232012700231
3.3%
234716779618
1.9%
287321276531
3.3%
ValueCountFrequency (%)
887768939131
3.3%
879200966529
3.1%
858381505931
3.3%
837856320031
3.3%
825324287919
2.0%
805347532831
3.3%
708636192631
3.3%
700774417126
2.8%
696218106731
3.3%
677588895526
2.8%

ActivityDate
Categorical

Uniform 

Distinct31
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
4/12/2016
 
33
4/14/2016
 
33
4/15/2016
 
33
4/13/2016
 
33
4/23/2016
 
32
Other values (26)
776 

Length

Max length9
Median length9
Mean length8.7255319
Min length8

Characters and Unicode

Total characters8202
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4/12/2016
2nd row4/13/2016
3rd row4/14/2016
4th row4/15/2016
5th row4/16/2016

Common Values

ValueCountFrequency (%)
4/12/201633
 
3.5%
4/14/201633
 
3.5%
4/15/201633
 
3.5%
4/13/201633
 
3.5%
4/23/201632
 
3.4%
4/29/201632
 
3.4%
4/28/201632
 
3.4%
4/26/201632
 
3.4%
4/25/201632
 
3.4%
4/24/201632
 
3.4%
Other values (21)616
65.5%

Length

2026-01-09T17:00:12.606040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4/12/201633
 
3.5%
4/15/201633
 
3.5%
4/13/201633
 
3.5%
4/14/201633
 
3.5%
4/22/201632
 
3.4%
4/21/201632
 
3.4%
4/16/201632
 
3.4%
4/18/201632
 
3.4%
4/19/201632
 
3.4%
4/20/201632
 
3.4%
Other values (21)616
65.5%

Most occurring characters

ValueCountFrequency (%)
/1880
22.9%
21375
16.8%
11357
16.5%
61033
12.6%
01029
12.5%
4705
 
8.6%
5423
 
5.2%
3125
 
1.5%
793
 
1.1%
991
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)8202
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/1880
22.9%
21375
16.8%
11357
16.5%
61033
12.6%
01029
12.5%
4705
 
8.6%
5423
 
5.2%
3125
 
1.5%
793
 
1.1%
991
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)8202
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/1880
22.9%
21375
16.8%
11357
16.5%
61033
12.6%
01029
12.5%
4705
 
8.6%
5423
 
5.2%
3125
 
1.5%
793
 
1.1%
991
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)8202
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/1880
22.9%
21375
16.8%
11357
16.5%
61033
12.6%
01029
12.5%
4705
 
8.6%
5423
 
5.2%
3125
 
1.5%
793
 
1.1%
991
 
1.1%

TotalSteps
Real number (ℝ)

High correlation  Zeros 

Distinct842
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7637.9106
Minimum0
Maximum36019
Zeros77
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:12.641503image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13789.75
median7405.5
Q310727
95-th percentile15485.1
Maximum36019
Range36019
Interquartile range (IQR)6937.25

Descriptive statistics

Standard deviation5087.1507
Coefficient of variation (CV)0.66603957
Kurtosis1.1691112
Mean7637.9106
Median Absolute Deviation (MAD)3446.5
Skewness0.65289494
Sum7179636
Variance25879103
MonotonicityNot monotonic
2026-01-09T17:00:12.683472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
077
 
8.2%
2442
 
0.2%
67082
 
0.2%
91672
 
0.2%
61752
 
0.2%
105382
 
0.2%
15102
 
0.2%
85382
 
0.2%
79372
 
0.2%
43632
 
0.2%
Other values (832)845
89.9%
ValueCountFrequency (%)
077
8.2%
41
 
0.1%
81
 
0.1%
91
 
0.1%
161
 
0.1%
171
 
0.1%
291
 
0.1%
311
 
0.1%
421
 
0.1%
441
 
0.1%
ValueCountFrequency (%)
360191
0.1%
293261
0.1%
277451
0.1%
236291
0.1%
231861
0.1%
229881
0.1%
227701
0.1%
223591
0.1%
222441
0.1%
220261
0.1%

TotalDistance
Real number (ℝ)

High correlation  Zeros 

Distinct615
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4897021
Minimum0
Maximum28.030001
Zeros78
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:12.728626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.6199999
median5.2449999
Q37.7125
95-th percentile11.6565
Maximum28.030001
Range28.030001
Interquartile range (IQR)5.0925001

Descriptive statistics

Standard deviation3.9246059
Coefficient of variation (CV)0.71490325
Kurtosis3.1130184
Mean5.4897021
Median Absolute Deviation (MAD)2.5600001
Skewness1.1262736
Sum5160.32
Variance15.402532
MonotonicityNot monotonic
2026-01-09T17:00:12.765527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
078
 
8.3%
2.5999999055
 
0.5%
0.0099999997765
 
0.5%
3.9100000864
 
0.4%
4.9499998094
 
0.4%
1.7899999624
 
0.4%
4.3299999244
 
0.4%
2.6800000674
 
0.4%
3.509999994
 
0.4%
4.9000000954
 
0.4%
Other values (605)824
87.7%
ValueCountFrequency (%)
078
8.3%
0.0099999997765
 
0.5%
0.019999999551
 
0.1%
0.029999999332
 
0.2%
0.039999999111
 
0.1%
0.079999998211
 
0.1%
0.090000003581
 
0.1%
0.10000000151
 
0.1%
0.10999999941
 
0.1%
0.12999999521
 
0.1%
ValueCountFrequency (%)
28.030000691
0.1%
26.719999311
0.1%
25.290000921
0.1%
20.649999621
0.1%
20.399999621
0.1%
19.559999471
0.1%
19.340000151
0.1%
18.979999541
0.1%
18.251
0.1%
18.110000611
0.1%

TrackerDistance
Real number (ℝ)

High correlation  Zeros 

Distinct613
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4753511
Minimum0
Maximum28.030001
Zeros78
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:12.804205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.6199999
median5.2449999
Q37.71
95-th percentile11.6565
Maximum28.030001
Range28.030001
Interquartile range (IQR)5.0900002

Descriptive statistics

Standard deviation3.9072759
Coefficient of variation (CV)0.71361195
Kurtosis3.2038891
Mean5.4753511
Median Absolute Deviation (MAD)2.5550003
Skewness1.1345496
Sum5146.83
Variance15.266805
MonotonicityNot monotonic
2026-01-09T17:00:12.840084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
078
 
8.3%
2.5999999055
 
0.5%
0.0099999997765
 
0.5%
3.9100000864
 
0.4%
2.6800000674
 
0.4%
1.7899999624
 
0.4%
4.3299999244
 
0.4%
4.9499998094
 
0.4%
3.509999994
 
0.4%
8.7399997714
 
0.4%
Other values (603)824
87.7%
ValueCountFrequency (%)
078
8.3%
0.0099999997765
 
0.5%
0.019999999551
 
0.1%
0.029999999332
 
0.2%
0.039999999111
 
0.1%
0.079999998211
 
0.1%
0.090000003581
 
0.1%
0.10000000151
 
0.1%
0.10999999941
 
0.1%
0.12999999521
 
0.1%
ValueCountFrequency (%)
28.030000691
0.1%
26.719999311
0.1%
25.290000921
0.1%
20.649999621
0.1%
20.399999621
0.1%
19.559999471
0.1%
19.340000151
0.1%
18.979999541
0.1%
18.251
0.1%
18.110000611
0.1%

LoggedActivitiesDistance
Real number (ℝ)

Zeros 

Distinct19
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10817094
Minimum0
Maximum4.942142
Zeros908
Zeros (%)96.6%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:12.869490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4.942142
Range4.942142
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.61989652
Coefficient of variation (CV)5.7307121
Kurtosis41.295941
Mean0.10817094
Median Absolute Deviation (MAD)0
Skewness6.2974404
Sum101.68068
Variance0.38427169
MonotonicityNot monotonic
2026-01-09T17:00:12.896600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0908
96.6%
2.0921471129
 
1.0%
2.2530810837
 
0.7%
4.0816922191
 
0.1%
4.8617920881
 
0.1%
4.8782320021
 
0.1%
4.9123678211
 
0.1%
2.8323259351
 
0.1%
4.9111461641
 
0.1%
4.8856048581
 
0.1%
Other values (9)9
 
1.0%
ValueCountFrequency (%)
0908
96.6%
1.9595960381
 
0.1%
2.0921471129
 
1.0%
2.2530810837
 
0.7%
2.7851750851
 
0.1%
2.8323259351
 
0.1%
3.1678218841
 
0.1%
3.2854149341
 
0.1%
4.0816922191
 
0.1%
4.8513069151
 
0.1%
ValueCountFrequency (%)
4.942142011
0.1%
4.9305500981
0.1%
4.9248409271
0.1%
4.9123678211
0.1%
4.9111461641
0.1%
4.8856048581
0.1%
4.8782320021
0.1%
4.8697829251
0.1%
4.8617920881
0.1%
4.8513069151
0.1%

VeryActiveDistance
Real number (ℝ)

High correlation  Zeros 

Distinct333
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5026809
Minimum0
Maximum21.92
Zeros413
Zeros (%)43.9%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:12.929228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.20999999
Q32.0524999
95-th percentile6.4030001
Maximum21.92
Range21.92
Interquartile range (IQR)2.0524999

Descriptive statistics

Standard deviation2.6589412
Coefficient of variation (CV)1.769465
Kurtosis11.910951
Mean1.5026809
Median Absolute Deviation (MAD)0.20999999
Skewness2.99617
Sum1412.52
Variance7.0699681
MonotonicityNot monotonic
2026-01-09T17:00:12.968160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0413
43.9%
0.07000000039
 
1.0%
0.059999998666
 
0.6%
0.14000000065
 
0.5%
0.33000001315
 
0.5%
0.34000000364
 
0.4%
1.0599999434
 
0.4%
0.36000001434
 
0.4%
1.009999994
 
0.4%
2.7899999624
 
0.4%
Other values (323)482
51.3%
ValueCountFrequency (%)
0413
43.9%
0.019999999552
 
0.2%
0.039999999111
 
0.1%
0.050000000753
 
0.3%
0.059999998666
 
0.6%
0.07000000039
 
1.0%
0.079999998214
 
0.4%
0.090000003581
 
0.1%
0.10999999943
 
0.3%
0.11999999733
 
0.3%
ValueCountFrequency (%)
21.920000081
0.1%
21.659999851
0.1%
13.399999621
0.1%
13.260000231
0.1%
13.239999771
0.1%
13.220000271
0.1%
13.130000111
0.1%
13.069999691
0.1%
12.789999961
0.1%
12.539999961
0.1%

ModeratelyActiveDistance
Real number (ℝ)

High correlation  Zeros 

Distinct211
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.56754255
Minimum0
Maximum6.48
Zeros386
Zeros (%)41.1%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:13.006621image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.23999999
Q30.80000001
95-th percentile2.1300001
Maximum6.48
Range6.48
Interquartile range (IQR)0.80000001

Descriptive statistics

Standard deviation0.88358032
Coefficient of variation (CV)1.556853
Kurtosis10.125629
Mean0.56754255
Median Absolute Deviation (MAD)0.23999999
Skewness2.7711936
Sum533.49
Variance0.78071418
MonotonicityNot monotonic
2026-01-09T17:00:13.045456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0386
41.1%
0.2000000039
 
1.0%
0.28000000129
 
1.0%
0.4000000069
 
1.0%
0.258
 
0.9%
0.31000000248
 
0.9%
0.93000000728
 
0.9%
0.41999998698
 
0.9%
0.27000001077
 
0.7%
0.56999999287
 
0.7%
Other values (201)481
51.2%
ValueCountFrequency (%)
0386
41.1%
0.0099999997761
 
0.1%
0.019999999551
 
0.1%
0.029999999333
 
0.3%
0.039999999113
 
0.3%
0.050000000753
 
0.3%
0.059999998663
 
0.3%
0.07000000032
 
0.2%
0.079999998214
 
0.4%
0.090000003582
 
0.2%
ValueCountFrequency (%)
6.4800000191
 
0.1%
6.2100000381
 
0.1%
5.5999999051
 
0.1%
5.4000000951
 
0.1%
5.2399997711
 
0.1%
5.1199998861
 
0.1%
4.5799999241
 
0.1%
4.5599999431
 
0.1%
4.3499999051
 
0.1%
4.219999793
0.3%

LightActiveDistance
Real number (ℝ)

High correlation  Zeros 

Distinct491
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3408191
Minimum0
Maximum10.71
Zeros85
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:13.082544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.945
median3.3649999
Q34.7825001
95-th percentile6.462
Maximum10.71
Range10.71
Interquartile range (IQR)2.8375001

Descriptive statistics

Standard deviation2.0406554
Coefficient of variation (CV)0.61082486
Kurtosis-0.18030027
Mean3.3408191
Median Absolute Deviation (MAD)1.4200002
Skewness0.18224747
Sum3140.37
Variance4.1642744
MonotonicityNot monotonic
2026-01-09T17:00:13.123619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
085
 
9.0%
4.1799998286
 
0.6%
3.1700000766
 
0.6%
4.8800001146
 
0.6%
3.2300000196
 
0.6%
3.9400000575
 
0.5%
3.259999995
 
0.5%
0.0099999997765
 
0.5%
4.4600000385
 
0.5%
5.4099998475
 
0.5%
Other values (481)806
85.7%
ValueCountFrequency (%)
085
9.0%
0.0099999997765
 
0.5%
0.019999999551
 
0.1%
0.029999999333
 
0.3%
0.039999999111
 
0.1%
0.059999998661
 
0.1%
0.090000003581
 
0.1%
0.10000000151
 
0.1%
0.10999999941
 
0.1%
0.12999999522
 
0.2%
ValueCountFrequency (%)
10.710000041
0.1%
10.569999691
0.1%
10.300000191
0.1%
9.4799995421
0.1%
9.4600000381
0.1%
8.9700002671
0.1%
8.7899999621
0.1%
8.6800003051
0.1%
8.4099998471
0.1%
8.2700004581
0.1%

SedentaryActiveDistance
Real number (ℝ)

Zeros 

Distinct9
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001606383
Minimum0
Maximum0.11
Zeros858
Zeros (%)91.3%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:13.150910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.0099999998
Maximum0.11
Range0.11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0073461763
Coefficient of variation (CV)4.5731164
Kurtosis99.127446
Mean0.001606383
Median Absolute Deviation (MAD)0
Skewness8.5898992
Sum1.51
Variance5.3966306 × 10-5
MonotonicityNot monotonic
2026-01-09T17:00:13.174752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0858
91.3%
0.00999999977650
 
5.3%
0.0199999995521
 
2.2%
0.029999999334
 
0.4%
0.050000000753
 
0.3%
0.07000000031
 
0.1%
0.039999999111
 
0.1%
0.10999999941
 
0.1%
0.10000000151
 
0.1%
ValueCountFrequency (%)
0858
91.3%
0.00999999977650
 
5.3%
0.0199999995521
 
2.2%
0.029999999334
 
0.4%
0.039999999111
 
0.1%
0.050000000753
 
0.3%
0.07000000031
 
0.1%
0.10000000151
 
0.1%
0.10999999941
 
0.1%
ValueCountFrequency (%)
0.10999999941
 
0.1%
0.10000000151
 
0.1%
0.07000000031
 
0.1%
0.050000000753
 
0.3%
0.039999999111
 
0.1%
0.029999999334
 
0.4%
0.0199999995521
 
2.2%
0.00999999977650
 
5.3%
0858
91.3%

VeryActiveMinutes
Real number (ℝ)

High correlation  Zeros 

Distinct122
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.164894
Minimum0
Maximum210
Zeros409
Zeros (%)43.5%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:13.206337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q332
95-th percentile93.05
Maximum210
Range210
Interquartile range (IQR)32

Descriptive statistics

Standard deviation32.844803
Coefficient of variation (CV)1.551853
Kurtosis5.7780701
Mean21.164894
Median Absolute Deviation (MAD)4
Skewness2.1761432
Sum19895
Variance1078.7811
MonotonicityNot monotonic
2026-01-09T17:00:13.242577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0409
43.5%
123
 
2.4%
218
 
1.9%
316
 
1.7%
815
 
1.6%
614
 
1.5%
1114
 
1.5%
1913
 
1.4%
513
 
1.4%
1412
 
1.3%
Other values (112)393
41.8%
ValueCountFrequency (%)
0409
43.5%
123
 
2.4%
218
 
1.9%
316
 
1.7%
410
 
1.1%
513
 
1.4%
614
 
1.5%
711
 
1.2%
815
 
1.6%
97
 
0.7%
ValueCountFrequency (%)
2101
0.1%
2071
0.1%
2001
0.1%
1941
0.1%
1861
0.1%
1841
0.1%
1371
0.1%
1321
0.1%
1291
0.1%
1252
0.2%

FairlyActiveMinutes
Real number (ℝ)

High correlation  Zeros 

Distinct81
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.564894
Minimum0
Maximum143
Zeros384
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:13.281099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q319
95-th percentile51
Maximum143
Range143
Interquartile range (IQR)19

Descriptive statistics

Standard deviation19.987404
Coefficient of variation (CV)1.4734656
Kurtosis7.9957314
Mean13.564894
Median Absolute Deviation (MAD)6
Skewness2.479492
Sum12751
Variance399.49632
MonotonicityNot monotonic
2026-01-09T17:00:13.318234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0384
40.9%
836
 
3.8%
623
 
2.4%
523
 
2.4%
1622
 
2.3%
720
 
2.1%
1019
 
2.0%
919
 
2.0%
1318
 
1.9%
1118
 
1.9%
Other values (71)358
38.1%
ValueCountFrequency (%)
0384
40.9%
110
 
1.1%
28
 
0.9%
39
 
1.0%
414
 
1.5%
523
 
2.4%
623
 
2.4%
720
 
2.1%
836
 
3.8%
919
 
2.0%
ValueCountFrequency (%)
1431
 
0.1%
1251
 
0.1%
1221
 
0.1%
1161
 
0.1%
1151
 
0.1%
1131
 
0.1%
981
 
0.1%
961
 
0.1%
955
0.5%
941
 
0.1%

LightlyActiveMinutes
Real number (ℝ)

High correlation  Zeros 

Distinct335
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.81277
Minimum0
Maximum518
Zeros84
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:13.355282image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1127
median199
Q3264
95-th percentile369.05
Maximum518
Range518
Interquartile range (IQR)137

Descriptive statistics

Standard deviation109.1747
Coefficient of variation (CV)0.56622132
Kurtosis-0.36011793
Mean192.81277
Median Absolute Deviation (MAD)69
Skewness-0.037929343
Sum181244
Variance11919.115
MonotonicityNot monotonic
2026-01-09T17:00:13.393634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
084
 
8.9%
20612
 
1.3%
25810
 
1.1%
1959
 
1.0%
2148
 
0.9%
1397
 
0.7%
2387
 
0.7%
1417
 
0.7%
1997
 
0.7%
2277
 
0.7%
Other values (325)782
83.2%
ValueCountFrequency (%)
084
8.9%
13
 
0.3%
24
 
0.4%
33
 
0.3%
41
 
0.1%
93
 
0.3%
102
 
0.2%
111
 
0.1%
122
 
0.2%
151
 
0.1%
ValueCountFrequency (%)
5181
0.1%
5131
0.1%
5121
0.1%
4871
0.1%
4801
0.1%
4751
0.1%
4611
0.1%
4581
0.1%
4481
0.1%
4391
0.1%

SedentaryMinutes
Real number (ℝ)

Distinct549
Distinct (%)58.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean991.21064
Minimum0
Maximum1440
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:13.428988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile536.7
Q1729.75
median1057.5
Q31229.5
95-th percentile1440
Maximum1440
Range1440
Interquartile range (IQR)499.75

Descriptive statistics

Standard deviation301.26744
Coefficient of variation (CV)0.30393887
Kurtosis-0.66595003
Mean991.21064
Median Absolute Deviation (MAD)261
Skewness-0.29449809
Sum931738
Variance90762.068
MonotonicityNot monotonic
2026-01-09T17:00:13.472438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144079
 
8.4%
11827
 
0.7%
6926
 
0.6%
11125
 
0.5%
11315
 
0.5%
11225
 
0.5%
11055
 
0.5%
7095
 
0.5%
11195
 
0.5%
7285
 
0.5%
Other values (539)813
86.5%
ValueCountFrequency (%)
01
0.1%
21
0.1%
131
0.1%
481
0.1%
1111
0.1%
1251
0.1%
1271
0.1%
2181
0.1%
2221
0.1%
2411
0.1%
ValueCountFrequency (%)
144079
8.4%
14393
 
0.3%
14383
 
0.3%
14372
 
0.2%
14311
 
0.1%
14302
 
0.2%
14281
 
0.1%
14231
 
0.1%
14201
 
0.1%
14131
 
0.1%

Calories
Real number (ℝ)

High correlation 

Distinct734
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2303.6096
Minimum0
Maximum4900
Zeros4
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2026-01-09T17:00:13.511423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1372.85
Q11828.5
median2134
Q32793.25
95-th percentile3654.25
Maximum4900
Range4900
Interquartile range (IQR)964.75

Descriptive statistics

Standard deviation718.16686
Coefficient of variation (CV)0.3117572
Kurtosis0.62502694
Mean2303.6096
Median Absolute Deviation (MAD)467
Skewness0.42245048
Sum2165393
Variance515763.64
MonotonicityNot monotonic
2026-01-09T17:00:13.556218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198013
 
1.4%
206311
 
1.2%
18419
 
1.0%
16889
 
1.0%
13478
 
0.9%
22254
 
0.4%
18194
 
0.4%
20444
 
0.4%
19224
 
0.4%
04
 
0.4%
Other values (724)870
92.6%
ValueCountFrequency (%)
04
0.4%
521
 
0.1%
571
 
0.1%
1201
 
0.1%
2571
 
0.1%
4031
 
0.1%
6651
 
0.1%
7411
 
0.1%
9281
 
0.1%
10021
 
0.1%
ValueCountFrequency (%)
49001
0.1%
45521
0.1%
45471
0.1%
45461
0.1%
45011
0.1%
43981
0.1%
43921
0.1%
42741
0.1%
42361
0.1%
41631
0.1%

Interactions

2026-01-09T17:00:11.932203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.267503image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.824875image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.324495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.784175image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.251128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.850450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.312864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.808490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.298608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.815601image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.312833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.839160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.310567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.966599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.340288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.860732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.357520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.816705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.283533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.883370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.350214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.845005image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.334876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.848861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.367233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.874105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.346830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:12.000826image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.382104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.900747image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.391599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.851135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.318112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.919995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.388572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.881277image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.372286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.891181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.407807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.909097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.382823image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:12.035830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.418500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.934763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.422175image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.883343image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.354985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.951388image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.422029image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.914062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.407875image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.925300image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.442358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.940917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.417135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:12.067773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.457288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.968996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.453503image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.914263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.520574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.985866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.456036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.948713image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.447093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.960733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.476776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.973365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.451389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:12.100345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.495698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.003703image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.485433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.950625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.552003image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.017375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.490979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.991707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.483068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.993659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.511166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.007299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.490097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:12.130881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.531457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.037407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.518998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.983333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.583006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.048107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-01-09T17:00:10.622297image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.109457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.594183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:12.229460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:05.644780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.145927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:06.617063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.083568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-01-09T17:00:08.149541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-01-09T17:00:09.636183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-01-09T17:00:10.657767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.141576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.629460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-01-09T17:00:06.752921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.217705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:07.818411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.281275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:08.775244image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.262591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:09.775217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.277403image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:10.798184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.277307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-09T17:00:11.897484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-01-09T17:00:13.589706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ActivityDateCaloriesFairlyActiveMinutesIdLightActiveDistanceLightlyActiveMinutesLoggedActivitiesDistanceModeratelyActiveDistanceSedentaryActiveDistanceSedentaryMinutesTotalDistanceTotalStepsTrackerDistanceVeryActiveDistanceVeryActiveMinutes
ActivityDate1.0000.1190.0510.0000.0000.0000.0000.0160.0000.0970.0000.0000.0000.0000.000
Calories0.1191.0000.4350.4290.4650.2860.2260.4030.010-0.1520.6170.5590.6170.4970.540
FairlyActiveMinutes0.0510.4351.0000.1250.3450.2320.1330.980-0.103-0.3140.6850.6890.6860.7430.746
Id0.0000.4290.1251.0000.030-0.0840.2100.111-0.114-0.0640.1990.1580.1970.2230.251
LightActiveDistance0.0000.4650.3450.0301.0000.8780.1390.3610.142-0.4660.7150.7150.7140.2850.285
LightlyActiveMinutes0.0000.2860.232-0.0840.8781.0000.0570.2440.194-0.4800.5590.5810.5580.1580.152
LoggedActivitiesDistance0.0000.2260.1330.2100.1390.0571.0000.1570.010-0.0870.2030.1800.1930.2260.265
ModeratelyActiveDistance0.0160.4030.9800.1110.3610.2440.1571.000-0.096-0.3080.7010.7040.7010.7490.734
SedentaryActiveDistance0.0000.010-0.103-0.1140.1420.1940.010-0.0961.0000.0960.0130.0150.011-0.064-0.057
SedentaryMinutes0.097-0.152-0.314-0.064-0.466-0.480-0.087-0.3080.0961.000-0.414-0.428-0.415-0.235-0.241
TotalDistance0.0000.6170.6850.1990.7150.5590.2030.7010.013-0.4141.0000.9921.0000.7760.752
TotalSteps0.0000.5590.6890.1580.7150.5810.1800.7040.015-0.4280.9921.0000.9920.7700.749
TrackerDistance0.0000.6170.6860.1970.7140.5580.1930.7010.011-0.4151.0000.9921.0000.7750.751
VeryActiveDistance0.0000.4970.7430.2230.2850.1580.2260.749-0.064-0.2350.7760.7700.7751.0000.970
VeryActiveMinutes0.0000.5400.7460.2510.2850.1520.2650.734-0.057-0.2410.7520.7490.7510.9701.000

Missing values

2026-01-09T17:00:12.422248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-01-09T17:00:12.467476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

IdActivityDateTotalStepsTotalDistanceTrackerDistanceLoggedActivitiesDistanceVeryActiveDistanceModeratelyActiveDistanceLightActiveDistanceSedentaryActiveDistanceVeryActiveMinutesFairlyActiveMinutesLightlyActiveMinutesSedentaryMinutesCalories
015039603664/12/2016131628.508.500.01.880.556.060.025133287281985
115039603664/13/2016107356.976.970.01.570.694.710.021192177761797
215039603664/14/2016104606.746.740.02.440.403.910.0301118112181776
315039603664/15/201697626.286.280.02.141.262.830.029342097261745
415039603664/16/2016126698.168.160.02.710.415.040.036102217731863
515039603664/17/201697056.486.480.03.190.782.510.038201645391728
615039603664/18/2016130198.598.590.03.250.644.710.0421623311491921
715039603664/19/2016155069.889.880.03.531.325.030.050312647752035
815039603664/20/2016105446.686.680.01.960.484.240.028122058181786
915039603664/21/201698196.346.340.01.340.354.650.01982118381775
IdActivityDateTotalStepsTotalDistanceTrackerDistanceLoggedActivitiesDistanceVeryActiveDistanceModeratelyActiveDistanceLightActiveDistanceSedentaryActiveDistanceVeryActiveMinutesFairlyActiveMinutesLightlyActiveMinutesSedentaryMinutesCalories
93088776893915/3/2016108188.2100008.2100000.01.390.106.670.0119322911892817
93188776893915/4/20161819316.29999916.2999990.010.420.315.530.0066821211543477
93288776893915/5/20161405510.67000010.6700000.05.460.824.370.00671518811703052
93388776893915/6/20162172719.34000019.3400000.012.790.296.160.00961723210954015
93488776893915/7/2016123328.1300008.1300000.00.080.966.990.001052827110364142
93588776893915/8/2016106868.1100008.1100000.01.080.206.800.0017424511742847
93688776893915/9/20162022618.25000018.2500000.011.100.806.240.05731921711313710
93788776893915/10/2016107338.1500008.1500000.01.350.466.280.00181122411872832
93888776893915/11/20162142019.55999919.5599990.013.220.415.890.00881221311273832
93988776893915/12/201680646.1200006.1200000.01.820.044.250.002311377701849